5-ALA induced PpIX fluorescence guided surgery of gliomas: comparison of expert and machine learning based models

P. Leclerc; L. Alston; L. Mahieu-Williame; C. Ray; M. Hébert; P. Kantapareddy; C. Frindel; P. F. Brevet; D. Meyronet; J. Guyotat; D. Rousseau; B. Montcel

doi:10.1117/12.2546670

17 February 2020 5-ALA induced PpIX fluorescence guided surgery of gliomas: comparison of expert and machine learning based models

P. Leclerc, L. Alston, L. Mahieu-Williame, C. Ray, M. Hébert, P. Kantapareddy, C. Frindel, P. F. Brevet, D. Meyronet, J. Guyotat, D. Rousseau, B. Montcel

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Proceedings Volume 11225, Clinical and Translational Neurophotonics 2020; 112250D (2020) https://doi.org/10.1117/12.2546670
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Gliomas are diffuse brain tumors still hardly curable due to the difficulties to identify margins. 5-ALA induced PpIX fluorescence measurements enable to gain in sensitivity but are still limited to discriminate margin from healthy tissue. In this fluorescence spectroscopic study, we compare an expert-based model assuming that two states of PpIX contribute to total fluorescence and machine learning-based models. We show that machine learning retrieves the main features identified by the expert approach. We also show that machine learning approach slightly overpasses expert-based model for the identification of healthy tissues. These results might help to improve fluorescence-guided resection of gliomas by discriminating healthy tissues from tumor margins.

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P. Leclerc, L. Alston, L. Mahieu-Williame, C. Ray, M. Hébert, P. Kantapareddy, C. Frindel, P. F. Brevet, D. Meyronet, J. Guyotat, D. Rousseau, and B. Montcel "5-ALA induced PpIX fluorescence guided surgery of gliomas: comparison of expert and machine learning based models", Proc. SPIE 11225, Clinical and Translational Neurophotonics 2020, 112250D (17 February 2020); https://doi.org/10.1117/12.2546670

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